GamCheckResult

Container returned by GAM.gam_check(), bundling residual diagnostics with fit summary

Usage

Source

GamCheckResult(
    deviance_residuals,
    fitted_values,
    response,
    k_check,
    deviance_explained,
    scale,
    edf_total,
    n_obs,
)

statistics and basis-dimension adequacy checks.

This mirrors the console output of R mgcv’s gam.check(): it lets you inspect whether the residuals look well-behaved and whether any smooth’s basis dimension k was set too small (in which case the smooth may be under-fitting), all from a single object. Printing the result (or relying on its __repr__) gives a compact textual report; the individual attributes are also available for building custom diagnostic plots (see GAM.check()).

Attributes

deviance_residuals: numpy.ndarray

Deviance residuals, shape (n,). Should look approximately normal and homoscedastic for a well-specified model.

fitted_values: numpy.ndarray

Fitted values mu on the response scale, shape (n,).

response: numpy.ndarray

Observed response values y used for fitting, shape (n,).

k_check: list[KCheckResult]

One basis-dimension check per smooth term. Each entry reports a k-index and a simulation-based p-value; low p-values (typically flagged with *) suggest the smooth’s basis dimension k may be too small to capture the true function.

deviance_explained: float

Proportion of null deviance explained by the model, in [0, 1] (analogous to R-squared for non-Gaussian families).

scale: float

The estimated scale (dispersion) parameter phi.

edf_total: float

The total effective degrees of freedom across all model terms.

n_obs: int

The number of observations used in the fit.